In 2003, the National Institute for Occupational Safety and Health (NIOSH) conducted a nationwide anthropometric survey of 3,997 subjects. The resulting head and face measurements were used to develop an anthropometric database detailing the face size distributions of respirator users using both traditional measurement methods and three-dimensional (3D) scanning systems. This database was used to establish fit test panels to be incorporated into NIOSH respirator certification and international standards. One of the panels developed, called the principal component analysis (PCA) panel, uses the first two principal components obtained from a set of 10 facial dimensions (age and race adjusted) and divides user population into five face-size categories. These 10 dimensions are associated with respirator fit and leakage and can predict the remaining face dimensions as well. Respirators designed to fit these panels are expected to accommodate more than 95% of the current U.S. civilian workers.

From the 3,997 subje

Supplementary research data to the paper (rejected):

Davide Fantini, Federico Avanzini, Stavros Ntalampiras and Giorgio Presti (2023) "Automatic Extraction of Anthropometric Features for the Individualization of the Pinna-Related Transfer Function in the Median Plane"

The repository includes the research data generated and analyzed in the abovementioned paper describing a method for PRTF individualization. In particular, the following data are included:

README.md: instructions for the data

pinna_range_img.mat: pinna range images extracted from the 3D head meshes of the HUTUBS dataset

landmarks.mat: landmarks coordinates both manually annotated and automatically placed with ASM

anthropometry.mat: anthropometric parameters automatically extracted from both manually annotated and ASM-fitted landmarks

img_features.mat: image features pinna cavities extracted from both manually annotated and ASM-fitted landmarks

grnn_models.mat: Generalized Regression Neural Network (GRNN) models trained from both HUTUBS anthropometry and the proposed pinna features

predicted_dtf.mat: Directional Transfer Function (DTF) sets predicted from both HUTUBS anthropometry and the proposed pinna features

anthropometry_documentation.pdf: documentation of the pinna anthropometric parameters

auditory_model_complete_elevation_range.pdf: auditory model evaluation in the complete elevation range

The data are provided in the Matlab file format MAT. Nevertheless, the MAT files can be read with other programming languages, such as Python (scipy.io.loadmat).

A GitHub repository to automatically extract the pinna landmarks and features as described in the paper is available here.